SEARCH · USGS Science

Results for “Soil Systems”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50Linked to original sources

USGS2021

Evaluating a laboratory flume microbiome as a window into natural riverbed biogeochemistry

Riverbeds are hotspots for microbially-mediated reactions that exhibit pronounced variability in space and time. It is challenging to resolve biogeochemical mechanisms in natural riverbeds, as uncontrolled settings complicate data collection and interpretation. To overcome these challenges, laboratory flumes are often used as proxies for natural riverbed systems. Flumes capture spatiotemporal variability and thus allow for controlled investigations of riverbed biogeochemistry. These investigations implicitly rely on the assumption that the flume microbiome is similar to the microbiome of natural riverbeds. However, this assumption has not been tested and it is unknown how the microbiome of a flume compares to natural aquatic settings, including riverbeds. To evaluate the fundamental assumption that a flume hosts a microbiome similar to natural riverbed systems, we used 16s rRNA gene sequencing and publicly available data to compare the sediment microbiome of a single large laboratory flume to a wide variety of natural ecosystems including lake and marine sediments, river, lake, hyporheic, soil, and marine water, and bank and wetland soils. Richness and Shannon diversity metrics, analyses of variance, Bray-Curtis dissimilarity, and analysis of the common microbiomes between flume and river sediment all indicated that the flume microbiome more closely resembled natural riverbed sediments than other ecosystems, supporting the use of flume experiments for investigating natural microbially-mediated biogeochemical processes in riverbeds.

Frontiers in Water↗

USGS1982

Assessing mesquite-grass vegetation condition from Landsat

Landsat multispectral scanner (MSS) band values, band ratios, and vegetation index models were compared with selected rangeland vegetation parameters collected at six test sites within the honey mesquitellotebushlmixed grass association in north-central Texas. The comparisons at four dates showed that two vegetation index models, TV16 and GVI, are highly correlated (P = 0.01) with green yield, green cover, and plant moisture content. The green vegetation index (GVZ) developed by Kauth and Thomas (1976), was highly correlated and superior to other models in relationship to wet green yield, dry green yield, and cured vegetation cover. TV16, developed by Rouse et al. (1974), was more highly correlated with green vegetation cover and vegetation moisture content. Both TV16 and GVI are superior to other models in their relationship with green cover. None of the Landsat MSS parameters tested was significantly correlated with dry total yield, percent bare ground, or moisture of the soil measured at the surface or at a 20 cm depth. I t is concluded that Landsat MSS data are sensitive to seasonal changes in vegetation growth conditions and inherent ecological differences within a relatively unqorm vegetationlsoil system.

Texas↗

USGS2025

Wet meadow regeneration through restoration of biophysical feedbacks

Wet meadows are globally significant ecosystems that provide critical hydrological, ecological, and biogeochemical functions, yet their extent has declined dramatically due to land use changes and hydrologic alteration. These sedge-dominated wetlands exist at the drier end of the wetland gradient, maintained by shallow groundwater and periodic inundation. This paper is a global synthesis of the ecological, geomorphic, and hydrological dynamics of wet meadows, with an emphasis on alluvial systems, to inform effective restoration strategies. We compare wet meadows to other wetlands, classify them into palustrine, lacustrine, and alluvial types, then focus on alluvial wet meadows and discuss how their formation and persistence depend on ground and surface water interactions, sediment deposition and flow obstructions, all mediated by biological processes. In particular, we highlight the role of hydric graminoids in resisting erosion and maintaining soil cohesion, how beaver promote meadow persistence, and the significance of wet meadows as carbon sinks. We also present stratigraphic evidence demonstrating that incision, often triggered by anthropogenic activity or changing climate, is the primary mechanism of alluvial wet meadow degradation, resulting in water table decline and shifts in vegetation composition. Restoration requires reversing these incisional processes through techniques that elevate water tables, disperse flow and retain sediment—methods traditionally associated with either soil conservation or stream restoration. These include nature-based solutions that create obstructions such as beaver dams and their analogues, rock and wood-based obstructions and incision trench or gully filling and grading. Given their multifunctional value—including but not limited to flood attenuation, biodiversity support, and carbon sequestration—wet meadows warrant a focused restoration framework. This review advocates for a valley-floor scale restoration paradigm that integrates hydrological reconnection, sediment retention, and biological reinforcement to ensure long-term resilience of these systems in the face of changing climate and land use pressures.

Frontiers in Environmental Science↗

USGS2013

Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems

Hydrogeomorphic, vegetative, and biogeochemical processes interact in floodplains resulting in great complexity that provides opportunities to better understand linkages among physical and biological processes in ecosystems. Floodplains and their associated river systems are structured by four dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depends on improved understanding and predictive models of interactive system controls and behavior.

Book chapter↗

USGS2022

Plague and trace metals in natural systems

All pathogenic organisms are exposed to abiotic influences such as the microclimates and chemical constituents of their environments. Even those pathogens that exist primarily within their hosts or vectors can be influenced directly or indirectly. Yersinia pestis , the flea-borne bacterium causing plague, is influenced by climate and its survival in soil suggests a potentially strong influence of soil chemistry. We summarize a series of controlled studies conducted over four decades in Russia by Dr. Evgeny Rotshild and his colleagues that investigated correlations between trace metals in soils, plants, and insects, and the detection of plague in free-ranging small mammals. Trace metal concentrations in plots where plague was detected were up to 20-fold higher or lower compared to associated control plots, and these differences were >2-fold in 22 of 38 comparisons. The results were statistically supported in eight studies involving seven host species in three families and two orders of small mammals. Plague tended to be positively associated with manganese and cobalt, and the plague association was negative for copper, zinc, and molybdenum. In additional studies, these investigators detected similar connections between pasturellosis and concentrations of some chemical elements. A One Health narrative should recognize that the chemistry of soil and water may facilitate or impede epidemics in humans and epizootics in non-human animals.

International Journal of Environmental Research an↗

USGS2011

Evaluating the variability of sediment and nutrient loading from riverine systems into Texas estuaries and bays

The water quality in estuaries and bays and the health of these coastal ecosystems are affected by sediment and nutrient loads transported by streams. Large sediment loads delivered to an estuary or bay can degrade water quality. Concentrations of suspended sediment are affected by natural conditions (such as soil erosion and streambed resuspension) and can also be affected by human activities (such as development, timber harvesting, certain agricultural practices, and hydraulic alteration). An increased sediment load delivered to an estuary or bay can reduce water clarity and light penetration (Senus and others, 2005) in the water column. Senus and others (2005, p. 1) also note that nutrients are needed to sustain life, but excess nutrient loads from human activities may cause unbalanced and unhealthy changes in water quality that are harmful to aquatic organisms. Nitrogen and phosphorus are two known nutrients of concern. Poor water quality caused by an abundance of these nutrients can stimulate the excessive growth of phytoplankton, promote algal blooms, reduce dissolved oxygen levels, and cause fish kills.

Texas↗

USGS2015

User manuals for the Delaware River Basin Water Availability Tool for Environmental Resources (DRB–WATER) and associated WATER application utilities

The Water Availability Tool for Environmental Resources (WATER) is a decision support system (DSS) for the nontidal part of the Delaware River Basin (DRB) that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that have been parameterized using three hydrologic response units—forested, agricultural, and developed land cover. It is this integration that enables the regional hydrologic-modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model. The DSS provides a “historical” database, ideal for simulating streamflow for 2001–11, in addition to land-cover forecasts that focus on 2030 and 2060. The WATER Application Utilities are provided with the DSS and apply change factors for precipitation, temperature, and potential evapotranspiration to a 1981–2011 climatic record provided with the DSS. These change factors were derived from a suite of general circulation models (GCMs) and representative concentration pathway (RCP) emission scenarios. These change factors are based on 25-year monthly averages (normals) that are centere on 2030 and 2060. The WATER Application Utilities also can be used to apply a 2010 snapshot of water use for the DRB; a factorial approach enables scenario testing of increased or decreased water use for each simulation. Finally, the WATER Application Utilities can be used to reformat streamflow time series for input to statistical or reservoir management software.

Delaware, Maryland, New Jersey, New York, Pennsylv↗

USGS2016

Late Quaternary offset of alluvial fan surfaces along the Central Sierra Madre Fault, southern California

The Sierra Madre Fault is a reverse fault system along the southern flank of the San Gabriel Mountains near Los Angeles, California. This study focuses on the Central Sierra Madre Fault (CSMF) in an effort to provide numeric dating on surfaces with ages previously estimated from soil development alone. We have refined previous geomorphic mapping conducted in the western portion of the CSMF near Pasadena, CA, with the aid of new lidar data. This progress report focuses on our geochronology strategy employed in collecting samples and interpreting data to determine a robust suite of terrace surface ages. Sample sites for terrestrial cosmogenic nuclide and luminescence dating techniques were selected to be redundant and to be validated through relative geomorphic relationships between inset terrace levels. Additional sample sites were selected to evaluate the post-abandonment histories of terrace surfaces. We will combine lidar-derived displacement data with surface ages to estimate slip rates for the CSMF.

Conference Paper↗

USGS2009

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.

Jinsha watershed, Yangtze River↗

USGS2024

Drought prediction and water availability: A report on the 2022 USGS-NIDIS National Listening Session Series

The U.S. Geological Survey (USGS) and NOAA’s National Integrated Drought Information System (NIDIS) conducted a series of four Listening Sessions in 2022 – each with a different application or topical focus – to seek input on priorities and needs related to predicting water availability changes under drought conditions at national and regional scales. This input was gathered to help inform the USGS Drought Program, regional and national drought efforts at NIDIS, and other national drought efforts. The series started with a February 2022 kick-off that introduced the series of Listening Sessions being held from March through September 2022. This kickoff also provided an overview of the USGS Drought Program’s work to characterize hydrological (e.g., streamflow and groundwater) drought, drought variability, drivers, and trends over the past century. Participants in these Listening Sessions included diverse stakeholder representation and perspectives. The first of the four Listening Sessions focused on streamflow (March 3, 2022), and included a short introduction to the USGS national streamflow drought research, the properties of a national drought prediction system, as well as presentations by other agencies on different drought prediction and forecasting efforts. The second session focused on groundwater (May 5, 2022), and included presentations on groundwater drought, sustainable groundwater management, and improving our understanding of soil moisture, groundwater, and surface water drought. The third session focused on water use (July 14, 2022), and included a discussion of the different drought types, as well as an introduction to several key projects, including the USGS Upper Colorado River Basin Study, the Ogallala Data Directory project, and a multi-agency drought prediction partnership in Oklahoma. The fourth and final Listening Session focused on water availability prediction for ecosystems (September 8, 2022), and included presentations on the development of a national capacity for eco-hydrological and drought science, building climate resilience, and actionable ecodrought resources.

Report↗

USGS2010

Field note--Successful establishment of a phytoremediation system at a petroleum-hydrocarbon contaminated shallow aquifer--Trends, trials, and tribulations

We report the establishment of a mixed hybrid poplar ( Populus spp .) and willow ( Salix spp .) phytoremediation system at a fuel-contaminated site. Several approaches were used to balance competing goals of cost-effectiveness yet successful tree establishment without artificial irrigation or trenching. Bare root and unrooted cuttings were installed using either: (1) 1.2 m deep holes excavated with an 8 cm diameter auger using a direct-push rig and backfilled with the excavated, in situ soil; (2) 1.2 m deep holes created with a 23 cm diameter auger attached to a Bobcat rig and backfilled with clean topsoil from offsite; and (3) shallow holes between 15–30 cm deep that were created with a 1.3 cm diameter rod and no backfill. Tree mortality from initial plantings indicated contaminated zones not quantified in prior site investigations and remedial actions. Aquifer heterogeneity, underground utilities, and prior remediation infrastructure hampered the ability of the site to support a traditional experimental design. Total stem length and mortality were measured for all planted trees and were incorporated into a geographic information system. Planting early in the growing season, augering a larger diameter hole, and backfilling with clean, uncontaminated topsoil was cost effective and allowed for greater tree cutting growth and survival.

International Journal of Phytoremediation↗

USGS2002

Uranium-series dating of pedogenic silica and carbonate, Crater Flat, Nevada

A 230Th-234U-238U dating study on pedogenic silica-carbonate clast rinds and matrix laminae from alluvium in Crater Flat, Nevada was conducted using small-sample thermal-ionization mass spectrometry (TIMS) analyses on a large suite of samples. Though the 232Th content of these soils is not particularly low (mostly 0.1-9 ppm), the high U content of the silica component (mostly 4-26 ppm) makes them particularly suitable for 230Th/U dating on single, 10 to 200 mg totally-digested samples using TIMS. We observed that (1) both micro- (within-rind) and macro-stratigraphic (mappabe deposit) order of the 230Th/U ages were preserved in all cases; (2) back-calculated initial 234U/238U fall in a restricted range (typically 1.67??0.19), so that 234U/238U ages with errors of about 100 kyr (2??) could be reliably determined for the oldest, 400 to 1000 ka rinds: and (3) though 13 of the samples were >350 ka, only three showed evidence for an open-system history, even though the sensitivity of such old samples to isotopic disruption is very high. An attempt to use leach-residue techniques to separate pedogenic from detrital U and Th failed, yielding corrupt 230Th/U ages. We conclude that 230Th/U ages determined from totally dissolved, multiple sub-mm size subsamples provide more reliable estimates of soil chronology than methods employing larger samples, chemical enhancement of 238U/232Th, or isochrons. Copyright ?? 2002 Elsevier Science Ltd.

Geochimica et Cosmochimica Acta↗

USGS2024

Nitrogen load estimates from six nonpoint sources on Long Island, New York, from 1900 to 2019

Estimates of nitrogen loading from nonpoint sources on Long Island, New York, at or just below the land surface, are essential for assessing the current and future effects of nitrogen on the island’s drinking water and fresh and marine surface receiving waters. Annual estimates of nitrogen loading for the 120 years from 1900 to 2019 for major nonpoint nitrogen sources—septic systems, residential fertilizer, agricultural fertilizer, livestock waste, pet waste, and atmospheric deposition—were made by using a geographic information system to analyze, visualize, and process data sources, and format output data. This analysis provided spatial and temporal estimates of nitrogen loading derived from each nonpoint source at a 500- by 500-foot gridded resolution and represents the total mass of nitrogen applied on, or just below, the land surface annually from 1900 to 2019. These mass estimates are considered unattenuated as they do not reflect the various mechanisms of nitrogen loss, such as plant uptake, overland runoff, and chemical transformations in the soil and unsaturated zones that likely reduce the amount of nitrogen that reaches the water table. Island-wide and countywide summaries of the estimated nitrogen loading were analyzed to describe the long-term average nitrogen totals and the contributions from the six nonpoint sources. The island-wide average annual nitrogen load from 1900 to 2019 was 14.92 million kilograms (Mkg) nitrogen, which represents the aggregate of individual contributions from septic systems (4.15 Mkg), residential fertilizer (3.28 Mkg), agricultural fertilizer (3.19 Mkg), livestock waste (1.22 Mkg), pet waste (0.98 Mkg), and atmospheric deposition (2.10 Mkg). The island-wide average annual nitrogen load, normalized by area, was 4,100 kilograms nitrogen per square kilometer (kg N/km 2 ), which represents the aggregate of individual contributions from septic systems (1,100 kg N/km 2 ), residential fertilizer (910 kg N/km 2 ), agricultural fertilizer (880 kg N/km 2 ), livestock waste (340 kg N/km 2 ), pet waste (270 kg N/km 2 ), and atmospheric deposition (580 kg N/km 2 ).

New York↗

USGS2016

The National Wind Erosion Research Network: Building a standardized long-term data resource for aeolian research, modeling and land management

The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.

Arizona, California, Colorado, Idaho, North Dakota↗

USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗

USGS2011

Is the northern high-latitude land-based CO2 sink weakening?

Studies indicate that, historically, terrestrial ecosystems of the northern high-latitude region may have been responsible for up to 60% of the global net land-based sink for atmospheric CO2. However, these regions have recently experienced remarkable modification of the major driving forces of the carbon cycle, including surface air temperature warming that is significantly greater than the global average and associated increases in the frequency and severity of disturbances. Whether Arctic tundra and boreal forest ecosystems will continue to sequester atmospheric CO2 in the face of these dramatic changes is unknown. Here we show the results of model simulations that estimate a 41 Tg C yr-1 sink in the boreal land regions from 1997 to 2006, which represents a 73% reduction in the strength of the sink estimated for previous decades in the late 20th century. Our results suggest that CO 2 uptake by the region in previous decades may not be as strong as previously estimated. The recent decline in sink strength is the combined result of (1) weakening sinks due to warming-induced increases in soil organic matter decomposition and (2) strengthening sources from pyrogenic CO2 emissions as a result of the substantial area of boreal forest burned in wildfires across the region in recent years. Such changes create positive feedbacks to the climate system that accelerate global warming, putting further pressure on emission reductions to achieve atmospheric stabilization targets. Copyright 2011 by the American Geophysical Union.

Global Biogeochemical Cycles↗

USGS2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integrates in-situ measurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697 µ molCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Alaska↗

USGS2014

Soil, plant, and terrain effects on natural perchlorate distribution in a desert landscape

Perchlorate (ClO 4 − ) is a contaminant that occurs naturally throughout the world, but little is known about its distribution and interactions in terrestrial ecosystems. The objectives of this Amargosa Desert, Nevada study were to determine (i) the local-scale distribution of shallow-soil (0–30 cm) ClO 4 − with respect to shrub proximity (far and near) in three geomorphic settings (shoulder slope, footslope, and valley floor); (ii) the importance of soil, plant, and terrain variables on the hillslope-distribution of shallow-soil and creosote bush [ Larrea tridentata (Sessé & Moc. ex DC.) Coville] ClO 4 − ; and (iii) atmospheric (wet plus dry, including dust) deposition of ClO 4 − in relation to soil and plant reservoirs and cycling. Soil ClO 4 − ranged from 0.3 to 5.0 μg kg −1 . Within settings, valley floor ClO 4 − was 17× less near shrubs due in part to enhanced leaching, whereas shoulder and footslope values were ∼2× greater near shrubs. Hillslope regression models (soil, R 2 = 0.42; leaf, R 2 = 0.74) identified topographic and soil effects on ClO 4 − deposition, transport, and cycling. Selective plant uptake, bioaccumulation, and soil enrichment were evidenced by leaf ClO 4 − concentrations and Cl − /ClO 4 − molar ratios that were ∼8000× greater and 40× less, respectively, than soil values. Atmospheric deposition ClO 4 − flux was 343 mg ha −1 yr −1 , ∼10× that for published southwestern wet-deposition fluxes. Creosote bush canopy ClO 4 − (1310 mg ha−1) was identified as a previously unrecognized but important and active reservoir. Nitrate δ 18 O analyses of atmospheric deposition and soil supported the leaf-cycled–ClO 4 − input hypothesis. This study provides basic data on ClO 4 − distribution and cycling that are pertinent to the assessment of environmental impacts in desert ecosystems and broadly transferable to anthropogenically contaminated systems.

Nevada↗